Background/Purpose: Dermatomyositis (DM) is a multisystemic immune mediated disease presenting with heterogeneous clinical features. Disease monitoring in DM relies in part on biomarkers of muscle disease activity such as creatinine kinase (CK) which may be unreliable especially in patients with predominant extra-muscular involvement. Novel proteomic platforms have the potential to identify inflammatory biomarkers for personalized monitoring.The objective of this study was to determine whether the Olink Target 96 Inflammation panel could identify proteins associated with disease activity in DM.

Methods: Six DM patients from a multicenter inflammatory myopathy registry with available longitudinal biobanked sera were identified. All patients met the 2017 EULAR/ACR criteria for adult idiopathic inflammatory myopathy. Disease activity at each timepoint was categorized based on the International Myositis Assessment and Clinical Study (IMACS) physician global assessment (PhGA) as low (PhGA 0-3) or moderate/high (PhGA 4-10). The IMACS core set measures necessary to calculate the 2016 ACR/EULAR Total Improvement Score were extracted. Serum samples were analyzed using proximity extension technology (Olink Proteomics Inc., Watertown, MA), simultaneously targeting 92 proteins involved in inflammatory processes. Results were reported as normalized protein expression (NPX) values (log2 scale) with higher NPX values representing higher protein concentration in the sample. Paired comparisons of NPX results were made using t-tests with Benjamini-Hochberg correction for multiple testing.

Results: Six female DM patients with ages ranging from 34 to 53 years were included (Table 1). Clinical features at timepoint 1 included rash (n=6), muscle weakness (n=5), interstitial lung disease (n=5), Raynaud’s (n=3), arthritis (n=1) and dysphagia (n=1). Median CK was 326 U/L (range 41-6039 U/L). Autoantibodies included anti-MDA5, -TIF1y, -Mi2, -Ro52, and -Ku. At the first timepoint, 5 patients had moderate/high disease activity and at the second timepoint, 5 patients had low disease activity. Eleven proteins were significantly upregulated when results were compared based on disease activity status (moderate/high vs. low) (Figure 1). The strongest modulation (ΔNPX) was observed for monocyte chemoattractant proteins, MCP-2 (3.0, adj. p=0.02), MCP-1 (2.4, adj. p=0.02), MCP-4 (2.2, adj. p=0.02), and C-X-C motif chemokine 11 (CXCL11, –3.0, adj. p=0.05). Additional upregulated proteins (ΔNPX) included PD-L1 (1.27, adj. p=0.05) and CD40 (0.92, adj. p=0.05). Other proteins with significant upregulation (all adj. p=0.05) were CX3CL1 (1.57), CCL11 (1.42), IL-4 (1.1), IL-15RA (0.9) and CSF-1 (0.61).

Conclusion: Using longitudinal serum inflammatory profiles, we identified proteins upregulated when patients with DM have moderate/high disease activity. Those included chemokines involved in monocyte and T-cell recruitment that could represent potential biomarkers for disease monitoring. Further studies on a larger number of DM patients are required to understand the potential of longitudinal proteomic analyses to improve personalized monitoring in DM.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/longitudinal-serum-proteomic-profiles-a-step-closer-to-personalized-monitoring-in-dermatomyositis/